首页|University College London (UCL) Reports Findings in Machine Learning (Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review)
University College London (UCL) Reports Findings in Machine Learning (Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review)
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New research on Machine Learning is the subject of a report. According to news reporting out of London, United Kingdom, by NewsRx editors, research stated, “Machine learning (ML)- based risk prediction models hold the potential to support the health-care setting in several ways; however, use of such models is scarce. We aimed to review health-care professional (HCP) and patient perceptions of ML risk prediction models in published literature, to inform future risk prediction model development.” Our news journalists obtained a quote from the research from University College London (UCL), “Following database and citation searches, we identified 41 articles suitable for inclusion. Article quality varied with qualitative studies performing strongest. Overall, perceptions of ML risk prediction models were positive. HCPs and patients considered that models have the potential to add benefit in the health-care setting. However, reservations remain; for example, concerns regarding data quality for model development and fears of unintended consequences following ML model use. We identified that public views regarding these models might be more negative than HCPs and that concerns (eg, extra demands on workload) were not always borne out in practice. Conclusions are tempered by the low number of patient and public studies, the absence of participant ethnic diversity, and variation in article quality.”
LondonUnited KingdomEuropeCyborgsEmerging TechnologiesMachine LearningRisk and Prevention
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